Model fitting to divergence and diversity dynamics.

<p>AIC is Akaike's information criterion with a second order correction for small sample sizes <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000240#pcbi.1000240-Brurnham1" target="_blank">[61]</a> and SQ is the sum of squared errors; subindex F indicates the full model; S1 submodel 1; and S2 submodel 2. The parameters <i>d_S</i> and <i>d</i>_max are estimated from the full model (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000240#pcbi-1000240-g003" target="_blank">Figure 3C</a>), along with 95% CIs (brackets) obtained by bootstrapping divergence and diversity dynamics 10³ times. The preferred model has the lowest AIC value.